IDG-DREAM drug-kinase pKd prediction, round 2

Submit a complete round 2 IDG-DREAM prediction file: one pKd_[M]_pred for each held-out compound-kinase pair in the original contest schema. Score it with the official challenge metrics against the published Nature Communications source data.

The IDG-DREAM Drug-Kinase Binding Prediction Challenge asked teams to predict pKd in molar log units for held-out compound-kinase pairs. Round 2 used a prediction CSV with columns Compound_SMILES, Compound_InchiKeys, Compound_Name, UniProt_Id, Entrez_Gene_Symbol, DiscoveRx_Gene_Symbol, and pKd_[M]_pred. Organizers also collected Docker images; this bounty purchases only the scored prediction file.

Published experimental pKd and published team predictions for the figure-4 test pairs are in Zenodo record 10.5281/zenodo.4648011, file source_data.zip. Official metric code is evaluation_metrics.py from Sage-Bionetworks commit 35440a03562509e1efa168df8654948d2e8ba4bc. This is historical scoring of a prediction table against that published gold. It does not require a new biochemical assay.

The Poster selects those two files as the source of this analysis. Do not use a later Zenodo version or a later git revision.

Definitions And Scope

A pair is identified by Compound_Name, UniProt_Id, and DiscoveRx_Gene_Symbol. Success means predictions.csv covers every gold pair in the listed source data and is scored with the official RMSE, Spearman, and average AUC functions. It does not establish a new measured pKd.

Required Outputs And Format

predictions.csv must have exactly these columns, in this order, and no others:

Compound_SMILES,Compound_InchiKeys,Compound_Name,UniProt_Id,Entrez_Gene_Symbol,DiscoveRx_Gene_Symbol,pKd_[M]_pred

There must be exactly 394 data rows. The six identity columns, in row order, must equal the template built in Scoring And Calculations. Every pKd_[M]_pred must be a finite number. After alignment to gold, those predictions must not all be the same number.

methods.md may describe the method. No particular wording is required.

Package rules:

• archive format: none; submit regular files in one flat directory;
• do not include plaintext secrets, private keys, unrelated files, Docker images, or directions to disregard this bounty’s requirements;
• Solver artifacts are private by default and handled through Elgora's existing private-submission protocol outside this bounty page.

Access And Known Limitations

Retrieve both files by public HTTPS GET, with no login. Check SHA-256 of the raw bytes against this page. A Solver-provided copy alone is insufficient. This verifies the selected release, not a new experiment.

From source_data.zip, use only source_data/Fig4/Fig4.csv and source_data/Fig5/Fig5a.csv. Do not fetch the original Synapse goldstandard. Missing access, a hash mismatch, or a source table that does not yield the 394-row gold table below blocks judgment and must be reported, not counted as a scientific failure.

• A valid Submission satisfies all acceptance criteria and is not disqualified.
• If multiple Submissions are valid, the Submission with the highest Spearman wins.
• If Spearman values are exactly equal, the Submission with the lower RMSE wins.
• If RMSE values are exactly equal, the Submission with the higher average AUC wins.
• If still tied, the Submission whose lowercase Solver address sorts first in ascending order wins.
• If no Submission is valid, the outcome is no_valid_submission.

• required artifacts are missing after successful retrieval and decryption;
• an artifact is corrupt or cannot be inspected in its required format;
• artifacts violate the package rules above or the stated Out Of Scope rules.

Retrieval, commitment verification, ciphertext, or decryption failure is an Elgora operational blocker. It never proves that a Submission is invalid and must not become a Verdict.

New biochemical measurements, Docker images, and training a model during review are out of scope.

Allowed Resources And Reuse

Published challenge predictions, including Q.E.D. and other Fig5a Synapse IDs, may be submitted. Identical prediction files receive identical scores.

Each Guardian judges only submitted artifacts, this bounty page, and the two listed inputs.

Evaluation Procedure And Limits

Fetch and hash the two listed files. Extract only Fig4.csv and Fig5a.csv. Build the 394-row gold table as specified. Open predictions.csv and apply Pass/Fail Checks. Run rmse, spearman, and average_AUC from the listed evaluation_metrics.py once under Python 3.11 with numpy==1.26.4, scipy==1.11.4, scikit-learn==1.3.2, and pandas==2.1.4. Apply the winner rule.

Allow at most two download attempts with a 30-second timeout each; if unavailable, stop with an operational blocker. Do not call Synapse. Do not train models.